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Dagstuhl Seminar 22442

Toward Scientific Evidence Standards in Empirical Computer Science

( Oct 30 – Nov 04, 2022 )


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Please use the following short url to reference this page: https://www.dagstuhl.de/22442

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Motivation

Many scientific fields of study use formally established evidence standards during the peer review and evaluation process, such as CONSORT (http://www.consort-statement.org) in medicine, the What Works Clearinghouse (https://ies.ed.gov/ncee/wwc/) in education, or the APA Journal Article Reporting Standards (JARS) in psychology (https://apastyle.apa.org/jars). The basis for these standards is community agreement on what to report in empirical studies. Such standards achieve two key goals. First, they make it easier to compare studies, facilitating replications which can provide confidence that multiple research teams can obtain the same results. Second, they establish community agreement on how to report on and evaluate studies using different methodologies.

The discipline of computer science does not have formalized evidence standards, even for major conferences or journals. This Dagstuhl Seminar has three primary objectives:

  1. To establish a process for creating or adopting an existing evidence standard for empirical research in computer science.
  2. To build a community of scholars that can discuss what a general standard should include.
  3. To kickstart the discussion with scholars from software engineering, human computer interaction, and computer science education.

In order to better discuss and understand the implications of such standards across several empirical subfields of computer science and to facilitate adoption, our plan for the seminar includes having representatives from prominent journals in attendance.

Copyright Brett A. Becker, Christopher D. Hundhausen, Ciera Jaspan, Andreas Stefik, and Thomas Zimmermann

Participants

Classification
  • Computers and Society
  • Human-Computer Interaction
  • Software Engineering

Keywords
  • Community Evidence Standards
  • Human Factors